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Labor Market Flows and Vacancies in the Cross Section and Over Time

Author

Listed:
  • R. Jason Faberman

    (Federal Reserve Bank of Philadelphia)

  • John Haltiwanger

    (University of Maryland)

  • Steven J. Davis

    (University of Chicago)

Abstract

Many theoretical models of labor market search imply a tight link between worker flows (hires and separations), vacancies, and job flows (employer-level employment growth) at the employer level. Using establishment data from multiple sources for the U.S., we show that hiring, quit, layoff, and vacancy rates exhibit strong, highly nonlinear relationships to establishment growth in the cross section. These relationships, notably for vacancy and quit rates, vary with aggregate conditions. We also develop a framework for evaluating how well the implications of various models fit the data. Aggregate variations in hires and layoffs are well captured by models with tight links between worker and job flows. Aggregate variations in quits and vacancies are not. Specifications that allow the micro-level quit relationship to vary with aggregate conditions (consistent with models of endogenous quits) perform remarkably better. Finally, our framework provides methodology for producing a backcasted series of worker flow and vacancy rates, which we estimate over the 1990-2008 period.

Suggested Citation

  • R. Jason Faberman & John Haltiwanger & Steven J. Davis, 2010. "Labor Market Flows and Vacancies in the Cross Section and Over Time," 2010 Meeting Papers 1045, Society for Economic Dynamics.
    • Handle: RePEc:red:sed010:1045
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    References listed on IDEAS

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    Cited by:

    1. Steven Davis, 2010. "EconomicDynamics Interviews Steven Davis on Labor Market Dynamics," EconomicDynamics Newsletter, Review of Economic Dynamics, vol. 12(1), November.
    2. Fredrik Andersson & John C. Haltiwanger & Mark J. Kutzbach & Henry O. Pollakowski & Daniel H. Weinberg, 2018. "Job Displacement and the Duration of Joblessness: The Role of Spatial Mismatch," The Review of Economics and Statistics, MIT Press, vol. 100(2), pages 203-218, May.

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